Research involving the development of statistical methods for studying the structural impact of social interventions is proposed. These methods will be applied in a study of the impact of an experimental manipulation on the social position of mentally retarded children in regular classroom settings. The affective social structures of small-scale social systems are represented by social networks and the purpose of policy generated interventions is viewed as manipulating the position within this network of a selected individual (such as an EMR child) or a subset of individuals (such as an ethnic or racial group). Essentially, in this view, the analysis of social interventions involves the use of fine grain structural features as dependant variables. Contemporary approaches to such analyses preclude controlling for the simultaneous influence of multiple variables at the individual and group level known or suspected to influence structure. We propose to use stochastic digraph theory to develop practical methods for monitoring and evaluating the impact of interventions on small-scale systems which control for multiple determining variables. These methods will be used to analyze extant empirical data from an experimental intervention in which 37 third, fourth and fifth grade classrooms each containing one EMR (Educable Mentally Retarded) child were exposed, at random, to a socially integrative intervention or control situation. Attempts to acquire similar data on mainstreaming experiments are proposed for the purpose of pursuing a comparative analysis of factors promoting or retarding the effectiveness of interventions on the social structural position of mainstreamed children. Extensions to other policy relevant social interventions will also be explored.